Platform Architect (Data Analytics & Management) - Vice President

We are seeking an experienced Platform Architect to provide end-to-end architectural leadership for the Client360 enterprise data platform. The role will own the technical integrity, scalability, security, resilience, and evolution of a cloud-based architecture spanning source integration, batch and near-real-time ingestion, Databricks Lakehouse processing, data governance, serving APIs, analytics, application integration, DevSecOps, and observability. The architect will translate business and non-functional requirements into executable designs, guide engineering teams through implementation, and ensure alignment with enterprise standards and regulatory controls.

Architecture Scope:

• •Enterprise and operational data source connections through APIs, JDBC sources, extracts, and event-driven streams.
• •AWS-hosted data platform services, including VPC, Amazon S3, Glacier, IAM, Secrets Manager, and CloudWatch.
• •Databricks Lakehouse architecture using Delta Lake, Databricks Medallion Architecture, Spark, Scala, SQL Warehouse, and governed catalog capabilities.
• •Batch, near-real-time, pull-based, push-based, and event-driven integration patterns.
• •Serving and integration layers using REST APIs, Java/Spring Boot services, Redis, MuleSoft etc.
• •Engineering tools and platform operations using GitHub, Jenkins, JFrog Artifactory, Airflow, Grafana, Kibana, log analytics, and centralized authentication/SSO services.
• •AWS infrastructure and storage architecture across VPC networking, S3, Glacier, IAM, Secrets Manager, key management, encryption, lifecycle and tiering policies, replication, backup, resiliency, performance, and cost management.
• •Architecture documentation covering context, container, component, deployment, sequence, data-flow, threat, and operational views
• •Integration/deployment of reusable AI capability/use cases into the platform.

Key Responsibilities:

• •Own and maintain the end-to-end solution architecture, reference models, integration patterns, technology standards, and architectural decision records.
• •Convert business capabilities, data requirements, service-level objectives, security obligations, and regulatory constraints into scalable technical designs.
• •Define target-state and transition architectures across ingestion, processing, storage, governance, orchestration, serving, APIs, applications, analytics, and archival, including data placement, partitioning, lifecycle, tiering, replication, backup, retention, encryption, and cost-optimization strategies.
• •Evaluation/POCs on emerging tech for variety of functional use cases and technical scenarios.
• •Establish patterns for batch and near-real-time ingestion using APIs, JDBC, file transfers, Auto Loader, and event-driven mechanisms.
• •Own IAM and cloud security architecture across AWS and Databricks, including least-privilege role design, workload identities, service principals, role-based and attribute-based access, secrets and key management, private connectivity, encryption, segregation of duties, privileged-access controls, audit logging, policy enforcement, and periodic access reviews.
• •Define high-availability and disaster-recovery architecture across storage, compute, networking, data pipelines, catalogs, orchestration, APIs, and dependent applications; establish workload-tiered availability targets, RTO/RPO, multi-availability-zone and cross-region patterns, failover/failback procedures, backup validation, and regular resilience testing.
• •Lead capacity planning and scalability engineering by forecasting data growth, concurrency, pipeline volume, API demand, storage consumption, compute requirements, network throughput, and recovery capacity; define autoscaling, workload isolation, quotas, performance baselines, load-testing, and cost guardrails.
• •Architect reliable API and application integrations across Java/Spring Boot, MuleSoft, Redis, ReactJS, NodeJS, Tableau, chatbot, and external endpoints.
• •Lead non-functional design for availability, performance, scalability, recoverability, maintainability, observability, security, and cost efficiency.
• •Drive data governance, cataloging, lineage, classification, retention, access controls, and segregation-of-duties practices.
• •Set CI/CD and infrastructure automation standards using GitHub, Jenkins, Artifactory, and infrastructure as code; govern reusable modules, environment provisioning, policy-as-code, automated testing, security scanning, state management, drift detection, deployment promotion, rollback, and controlled change execution.
• •Define monitoring, logging, alerting, operational dashboards, support runbooks, and service health measures using CloudWatch, Grafana, Kibana, and log analytics.
• •Chair architecture and design reviews; identify risks, trade-offs, dependencies, technical debt, and remediation plans before implementation.
• •Partner with product owners, data engineers, application engineers, security, infrastructure, operations, governance, and enterprise architecture stakeholders.
• •Guide proofs of concept, technology evaluations, capacity planning, performance testing, production readiness reviews, and incident root-cause analysis.
• •Mentor technical leads and engineers, promote reusable patterns, and ensure implementation conforms to approved architecture.
• •Manage the architectural roadmap and continuously simplify the platform while improving automation, reliability, and total cost of ownership.

Qualifications and Experience:

• •20+ years of technology experience, including at least 10 years in architecture or senior technical leadership roles.
• •Demonstrated ownership of enterprise-scale cloud data platforms from design through production operation.
• •Experience in regulated or highly controlled environments, preferably financial services.
• •Track record of leading cross-functional teams and influencing senior engineering, product, security, risk, and operations stakeholders.
• •Strong written and verbal communication, with the ability to explain complex trade-offs to both technical and executive audiences.

Preferred Qualifications:

• •Databricks Platform Architect certification and/or AWS Solutions Architect – Professional or equivalent cloud architecture certification.
• •TOGAF or another recognized enterprise architecture certification.
• •Experience with infrastructure as code, automated policy enforcement, FinOps, and platform engineering.
• •Knowledge of master data management, customer-360 data products, data quality frameworks, and AI/ML operational governance.

Leadership Competencies:

• •Enterprise thinking with strong execution discipline.
• •Sound judgment in balancing delivery speed, engineering quality, risk, and cost.
• •Ability to challenge designs constructively and drive decisions through ambiguity.
• •Strong stakeholder management, facilitation, negotiation, and technical storytelling.
• •Commitment to engineering excellence, continuous improvement, and talent development.

Success Measures:

• •Architecture decisions are documented, approved, traceable, and consistently implemented across teams.
• •Critical platform services meet workload-tiered availability, latency, throughput, scalability, recovery, RTO/RPO, security, storage durability, and data-quality targets.
• •Production incidents, architectural exceptions, security findings, and recurring operational issues decline over time.
• •Delivery teams achieve predictable releases through reusable patterns, automated controls, and effective CI/CD.
• •Cloud and Databricks consumption is measurable, optimized, and aligned with workload value.
• •Governance, audit, classification, lineage, retention, and access-control requirements are demonstrably satisfied.
• •The platform roadmap supports new data sources, products, users, and workloads without disproportionate complexity or cost.

Are you the right candidate? Yes!

We truly believe in the power that comes from the diverse backgrounds and experiences our employees bring with them. Al